Artificial intelligence (AI) could help clinicians identify patients who would benefit from the treatment of Alzheimer's disease.
The team at MGH used deep learning a type of machine learning and artificial intelligence that uses large amounts of data and complex algorithms to train models and improve detection of the brain disease.
The AI was trained on brain magnetic resonance images (MRIs) collected from patients with and without Alzheimer’s disease who were seen at MGH before 2019.
Next, the group tested the model across five datasets – MGH post-2019, Brigham and Women’s Hospital pre- and post-2019, and outside systems pre- and post-2019 – to see if it could accurately detect Alzheimer’s disease based on real-world clinical data, regardless of hospital and time.
Overall, the research involved 11,103 images from 2,348 patients at risk for Alzheimer’s disease and 26,892 images from 8,456 patients without Alzheimer’s disease.
The results showed...